Write down the econometric model that this OLS regression estimates. Interpret the educ coefficient.  At how many average weekly hours worked is the marginal effect of hours on predicted wage equal to zero? What is the exact effect (in percent) of an increase of 10 years of education on predicted wage? What is the predicted monthly wage in US$ for a worker with 10 years of education, an IQ score of 100, who works on average 40 hours per week?

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ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
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Write down the econometric model that this OLS regression estimates.

Interpret the educ coefficient. 

At how many average weekly hours worked is the marginal effect of hours on predicted wage equal to zero?

What is the exact effect (in percent) of an increase of 10 years of education on predicted wage?

What is the predicted monthly wage in US$ for a worker with 10 years of education, an IQ score of 100, who works on average 40 hours per week? 

Source
SS
df
MS
Number of obs
935
=
F (4, 930)
36.82
Model
22.6467366
4
5.66168416
Prob > F
0.0000
Residual
143.009547
930
.153773706
R-squared
Adj R-squared
Root MSE
0.1367
0.1330
Total
165.656283
934
.177362188
.39214
lwage
Coef.
Std. Err.
P>|t|
[95% Conf. Interval]
educ
.0400982
.0068351
5.87
0.000
.0266843
.0535122
IQ
.005914
.0009967
5.93
0.000
.0039579
.0078701
hours
.0035899
.013037
0.28
0.783
-.0219954
.0291752
hours2
-.0000842
.0001298
-0.65
0.517
-.0003389
.0001706
cons
5.649044
.3240363
17.43
0.000
5.013117
6.284971
where Iwage is the natural logarithm of monthly wage in US$, educ is years of education, IQ
is points on an IQ intelligence test, hours is average weekly hours worked, and hours2 is
experience squared (hours * hours). Assume that MLR 1-6 hold.
Transcribed Image Text:Source SS df MS Number of obs 935 = F (4, 930) 36.82 Model 22.6467366 4 5.66168416 Prob > F 0.0000 Residual 143.009547 930 .153773706 R-squared Adj R-squared Root MSE 0.1367 0.1330 Total 165.656283 934 .177362188 .39214 lwage Coef. Std. Err. P>|t| [95% Conf. Interval] educ .0400982 .0068351 5.87 0.000 .0266843 .0535122 IQ .005914 .0009967 5.93 0.000 .0039579 .0078701 hours .0035899 .013037 0.28 0.783 -.0219954 .0291752 hours2 -.0000842 .0001298 -0.65 0.517 -.0003389 .0001706 cons 5.649044 .3240363 17.43 0.000 5.013117 6.284971 where Iwage is the natural logarithm of monthly wage in US$, educ is years of education, IQ is points on an IQ intelligence test, hours is average weekly hours worked, and hours2 is experience squared (hours * hours). Assume that MLR 1-6 hold.
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Follow-up Question
What is the exact effect (in percent) of an increase of 10 years of education on predicted wage?
What is the predicted monthly wage in US$ for a worker with 10 years of education, an IQ score of 100, who works on average
40 hours per week?
Source
SS
df
MS
Number of obs
935
F (4, 930)
36.82
Model
22.6467366
4
5.66168416
Prob > F
0.0000
Residual
143.009547
930
.153773706
R-squared
Adj R-squared
0.1367
0.1330
%3D
Total
165.656283
934
.177362188
Root MSE
.39214
lwage
Сoef.
Std. Err.
t
P> |t|
[95% Conf. Interval]
educ
0400982
.0068351
5.87
0.000
.0266843
.0535122
IQ
.005914
.0009967
5.93
0.000
.0039579
.0078701
hours
.0035899
.013037
0.28
0.783
-.0219954
.0291752
hours2
-.0000842
.0001298
-0.65
0.517
-.0003389
.0001706
cons
5.649044
.3240363
17.43
0.000
5.013117
6.284971
where Iwage is the natural logarithm of monthly wage in US$, educ is years of education, IQ
is points on an IQ intelligence test, hours is average weekly hours worked, and hours2 is
experience squared (hours * hours). Assume that MLR 1-6 hold.
Transcribed Image Text:What is the exact effect (in percent) of an increase of 10 years of education on predicted wage? What is the predicted monthly wage in US$ for a worker with 10 years of education, an IQ score of 100, who works on average 40 hours per week? Source SS df MS Number of obs 935 F (4, 930) 36.82 Model 22.6467366 4 5.66168416 Prob > F 0.0000 Residual 143.009547 930 .153773706 R-squared Adj R-squared 0.1367 0.1330 %3D Total 165.656283 934 .177362188 Root MSE .39214 lwage Сoef. Std. Err. t P> |t| [95% Conf. Interval] educ 0400982 .0068351 5.87 0.000 .0266843 .0535122 IQ .005914 .0009967 5.93 0.000 .0039579 .0078701 hours .0035899 .013037 0.28 0.783 -.0219954 .0291752 hours2 -.0000842 .0001298 -0.65 0.517 -.0003389 .0001706 cons 5.649044 .3240363 17.43 0.000 5.013117 6.284971 where Iwage is the natural logarithm of monthly wage in US$, educ is years of education, IQ is points on an IQ intelligence test, hours is average weekly hours worked, and hours2 is experience squared (hours * hours). Assume that MLR 1-6 hold.
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